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MotionLM Processed WOMD Dataset
A processed, lightweight version of the Waymo Open Motion Dataset (WOMD), prepared for training a MotionLM model.
The original WOMD scenarios have been transformed into compact PyTorch tensor shards (.pt.zst, zstd-compressed) so they can be streamed directly into the training loop without the overhead of decoding protobuf scenarios on the fly.
Splits
| Split | Shards | Size |
|---|---|---|
training |
1000 | ~114 GB |
validation |
150 | ~10 GB |
test |
150 | ~11 GB |
File naming follows {split}.{i}of{n}.pt.zst.
Usage
Used to train the MotionLM implementation at https://github.com/Mol2017/MotionLM. See that repository for the data loader, model code, and training scripts.
import torch
import zstandard as zstd
import io
with open("training/train.0of1000.pt.zst", "rb") as f:
decompressed = zstd.ZstdDecompressor().decompress(f.read())
batch = torch.load(io.BytesIO(decompressed))
Source
Derived from the Waymo Open Motion Dataset. Please consult the Waymo Open Dataset license for terms governing use of the underlying data.
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